Determination of Butyrate Synthesis Capacity in Gut Microbiota: Quantification of but Gene Abundance by qPCR in Fecal Samples

Butyrate is formed in the gut during bacterial fermentation of dietary fiber and is attributed numerous beneficial effects on the host metabolism. We aimed to develop a method for the assessment of functional capacity of gut microbiota butyrate synthesis based on the qPCR quantification of bacterial gene coding butyryl-CoA:acetate CoA-transferase, the key enzyme of butyrate synthesis. In silico, we identified bacteria possessing but gene among human gut microbiota by searching but coding sequences in available databases. We designed and validated six sets of degenerate primers covering all selected bacteria, based on their phylogenetic nearness and sequence similarity, and developed a method for gene abundance normalization in human fecal DNA. We determined but gene abundance in fecal DNA of subjects with opposing dietary patterns and metabolic phenotypes-lean vegans (VG) and healthy obese omnivores (OB) with known fecal microbiota and metabolome composition. We found higher but gene copy number in VG compared with OB, in line with higher fecal butyrate content in VG group. We further found a positive correlation between the relative abundance of target bacterial genera identified by next-generation sequencing and groups of but gene-containing bacteria determined by specific primers. In conclusion, this approach represents a simple and feasible tool for estimation of microbial functional capacity

Multi-omics signatures in new-onset diabetes predict metabolic response to dietary inulin: findings from an observational study followed by an interventional trial

AIM: The metabolic performance of the gut microbiota contributes to the onset of type 2 diabetes. However, targeted dietary interventions are limited by the highly variable inter-individual response. We hypothesized (1) that the composition of the complex gut microbiome and metabolome (MIME) differ across metabolic spectra (lean-obese-diabetes); (2) that specific MIME patterns could explain the differential responses to dietary inulin; and (3) that the response can be predicted based on baseline MIME signature and clinical characteristics. METHOD: Forty-nine patients with newly diagnosed pre/diabetes (DM), 66 metabolically healthy overweight/obese (OB), and 32 healthy lean (LH) volunteers were compared in a cross-sectional case-control study integrating clinical variables, dietary intake, gut microbiome, and fecal/serum metabolomes (16 S rRNA sequencing, metabolomics profiling). Subsequently, 27 DM were recruited for a predictive study: 3 months of dietary inulin (10 g/day) intervention. RESULTS: MIME composition was different between groups. While the DM and LH groups represented opposite poles of the abundance spectrum, OB was closer to DM. Inulin supplementation was associated with an overall improvement in glycemic indices, though the response was very variable, with a shift in microbiome composition toward a more favorable profile and increased serum butyric and propionic acid concentrations. The improved glycemic outcomes of inulin treatment were dependent on better baseline glycemic status and variables related to the gut microbiota, including the abundance of certain bacterial taxa (i.e., Blautia, Eubacterium halii group, Lachnoclostridium, Ruminiclostridium, Dialister, or Phascolarctobacterium), serum concentrations of branched-chain amino acid derivatives and asparagine, and fecal concentrations of indole and several other volatile organic compounds. CONCLUSION: We demonstrated that obesity is a stronger determinant of different MIME patterns than impaired glucose metabolism. The large inter-individual variability in the metabolic effects of dietary inulin was explained by differences in baseline glycemic status and MIME signatures. These could be further validated to personalize nutritional interventions in patients with newly diagnosed diabetes

Comparison of Inflammatory Response to Transgastric and Transcolonic NOTES

Aims. The aim of our study was to determine the physiologic impact of NOTES and to compare the transgastric and transcolonic approaches. Methods. Thirty pigs were randomized to transgastric, transcolonic, or laparoscopic peritoneoscopy. Blood was drawn and analyzed for C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), interleukin- (IL-) 1β, IL-6, WBCs, and platelets. Results. Endoscopic closure with an OTSC was successful in all 20 animals. The postoperative course was uneventful in all animals. CRP values rose on day 1 in all animals and slowly declined to baseline levels on day 14 with no differences between the groups (P>0.05, NS). The levels of TNF-α were significantly increased in the transcolonic group (P<0.01); however this difference was already present prior to the procedure and remained unchanged. No differences were observed in IL1-β and IL-6 values. There was a temporary rise of WBC on day 1 and of platelets on day 7 in all groups (P>0.05, NS). Conclusions. Transgastric, transcolonic, and laparoscopic peritoneoscopy resulted in similar changes in systemic inflammatory markers. Our findings do not support the assumption that NOTES is less invasive than laparoscopy

Serum miR-33a is associated with steatosis and inflammation in patients with non-alcoholic fatty liver disease after liver transplantation.

BACKGROUND & AIMS:MiR-33a has emerged as a critical regulator of lipid homeostasis in the liver. Genetic deficiency of miR-33a aggravates liver steatosis in a preclinical model of non-alcoholic fatty liver disease (NAFLD), and relative expression of miR-33a is increased in the livers of patients with non-alcoholic steatohepatitis (NASH). It was unknown whether miR-33a is detectable in the serum of patients with NAFLD. We sought to determine whether circulating miR-33a is associated with histological hepatic steatosis, inflammation, ballooning or fibrosis, and whether it could be used as a serum marker in patients with NAFLD/NASH. METHODS:We analysed circulating miR-33a using quantitative PCR in 116 liver transplant recipients who underwent post-transplant protocol liver biopsy. Regression analysis was used to determine association of serum miR-33a with hepatic steatosis, inflammation, ballooning and fibrosis in liver biopsy. RESULTS:Liver graft steatosis and inflammation, but not ballooning or fibrosis, were significantly associated with serum miR-33a, dyslipidemia and insulin resistance markers on univariate analysis. Multivariate analysis showed that steatosis was independently associated with serum miR-33a, ALT, glycaemia and waist circumference, whereas inflammation was independently associated with miR-33a, HbA1 and serum triglyceride levels. Receiver operating characteristic analysis showed that exclusion of serum miR-33a from multivariate analysis resulted in non-significant reduction of prediction model accuracy of liver steatosis or inflammation. CONCLUSIONS:Our data indicate that circulating miR-33a is an independent predictor of liver steatosis and inflammation in patients after liver transplantation. Although statistically significant, its contribution to the accuracy of prediction model employing readily available clinical and biochemical variables was limited in our cohort

Silymarin prevents acetaminophen-induced hepatotoxicity in mice - Fig 3

<p><b>Effect of APAP and SLM on CYP2E1 activity in vivo (A), mRNA expression (B), protein content (C) and CYPE1 activity in vitro (D, E).</b> Results represent mean ± SEM, n = 7. *p < 0.05, **p < 0.01, ***p < 0.001 APAP vs control. ^#p < 0.05, ^##p < 0.01 APAP + SLM vs APAP.</p

The Effect of Butyrate-Supplemented Parenteral Nutrition on Intestinal Defence Mechanisms and the Parenteral Nutrition-Induced Shift in the Gut Microbiota in the Rat Model

Butyrate produced by the intestinal microbiota is essential for proper functioning of the intestinal immune system. Total dependence on parenteral nutrition (PN) is associated with numerous adverse effects, including severe microbial dysbiosis and loss of important butyrate producers. We hypothesised that a lack of butyrate produced by the gut microbiota may be compensated by its supplementation in PN mixtures. We tested whether i.v. butyrate administration would (a) positively modulate intestinal defence mechanisms and (b) counteract PN-induced dysbiosis. Male Wistar rats were randomised to chow, PN, and PN supplemented with 9 mM butyrate (PN+But) for 12 days. Antimicrobial peptides, mucins, tight junction proteins, and cytokine expression were assessed by RT-qPCR. T-cell subpopulations in mesenteric lymph nodes (MLN) were analysed by flow cytometry. Microbiota composition was assessed in caecum content. Butyrate supplementation resulted in increased expression of tight junction proteins (ZO-1, claudin-7, E-cadherin), antimicrobial peptides (Defa 8, Rd5, RegIIIγ), and lysozyme in the ileal mucosa. Butyrate partially alleviated PN-induced intestinal barrier impairment and normalised IL-4, IL-10, and IgA mRNA expression. PN administration was associated with an increase in Tregs in MLN, which was normalised by butyrate. Butyrate increased the total number of CD4+ and decreased a relative amount of CD8+ memory T cells in MLN. Lack of enteral nutrition and PN administration led to a shift in caecal microbiota composition. Butyrate did not reverse the altered expression of most taxa but did influence the abundance of some potentially beneficial/pathogenic genera, which might contribute to its overall beneficial effect

Effect of APAP and SLM on reactive oxygen species production from submitochondrial particles in vitro.

<p>(A) ROS production from NADH -/+ AA; (B) ROS production from succinate -/+ AA. Results are expressed as a percent of basal levels (without substrate). Data are presented as a mean ± SEM, n = 7. *p < 0.05, ***p < 0.001 APAP vs control (succinate + AA); ^† p < 0.05 APAP + SLM vs APAP (only succinate); ^#p < 0.05, ^## p < 0.01 APAP + SLM vs APAP (succinate + AA).</p

Effect of APAP and SLM on lipid peroxidation in the liver.

<p>Data are given as mean ± SEM, n = 7. *p < 0.05 APAP vs control; ^#p < 0.05, ^##p < 0.01 APAP + SLM vs APAP.</p

Effect of APAP and SLM on RIP-3 expression.

<p>The liver homogenate was separated by SDS-ELFO, immunoblotted and the proteins of interest were detected using specific antibody.</p